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Book Discriminant Analysis and Applications

Download or read book Discriminant Analysis and Applications written by T. Cacoullos and published by Academic Press. This book was released on 2014-05-10 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discriminant Analysis and Applications comprises the proceedings of the NATO Advanced Study Institute on Discriminant Analysis and Applications held in Kifissia, Athens, Greece in June 1972. The book presents the theory and applications of Discriminant analysis, one of the most important areas of multivariate statistical analysis. This volume contains chapters that cover the historical development of discriminant analysis methods; logistic and quasi-linear discrimination; and distance functions. Medical and biological applications, and computer graphical analysis and graphical techniques for multidimensional data are likewise discussed. Statisticians, mathematicians, and biomathematicians will find the book very interesting.

Book Applied MANOVA and Discriminant Analysis

Download or read book Applied MANOVA and Discriminant Analysis written by Carl J. Huberty and published by John Wiley & Sons. This book was released on 2006-05-12 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete introduction to discriminant analysis--extensively revised, expanded, and updated This Second Edition of the classic book, Applied Discriminant Analysis, reflects and references current usage with its new title, Applied MANOVA and Discriminant Analysis. Thoroughly updated and revised, this book continues to be essential for any researcher or student needing to learn to speak, read, and write about discriminant analysis as well as develop a philosophy of empirical research and data analysis. Its thorough introduction to the application of discriminant analysis is unparalleled. Offering the most up-to-date computer applications, references, terms, and real-life research examples, the Second Edition also includes new discussions of MANOVA, descriptive discriminant analysis, and predictive discriminant analysis. Newer SAS macros are included, and graphical software with data sets and programs are provided on the book's related Web site. The book features: Detailed discussions of multivariate analysis of variance and covariance An increased number of chapter exercises along with selected answers Analyses of data obtained via a repeated measures design A new chapter on analyses related to predictive discriminant analysis Basic SPSS(r) and SAS(r) computer syntax and output integrated throughout the book Applied MANOVA and Discriminant Analysis enables the reader to become aware of various types of research questions using MANOVA and discriminant analysis; to learn the meaning of this field's concepts and terms; and to be able to design a study that uses discriminant analysis through topics such as one-factor MANOVA/DDA, assessing and describing MANOVA effects, and deleting and ordering variables.

Book Discriminant Analysis

Download or read book Discriminant Analysis written by William R. Klecka and published by SAGE. This book was released on 1980-08 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Background. Deriving the canonical discriminant functions. Interpreting the canonical discriminant functions. Classification procedures. Stepwise inclusion of variables. Concluding remarks.

Book Discriminant analysis and applications

Download or read book Discriminant analysis and applications written by Theophilos Cacoullos and published by . This book was released on 1973 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Data Analysis and Applications 2

Download or read book Data Analysis and Applications 2 written by Christos H. Skiadas and published by John Wiley & Sons. This book was released on 2019-03-07 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications. Volume 2 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into four parts: Part 1 examines (in)dependence relationships, innovation in the Nordic countries, dentistry journals, dependence among growth rates of GDP of V4 countries, emissions mitigation, and five-star ratings; Part 2 investigates access to credit for SMEs, gender-based impacts given Southern Europe’s economic crisis, and labor market transition probabilities; Part 3 looks at recruitment at university job-placement offices and the Program for International Student Assessment; and Part 4 examines discriminants, PageRank, and the political spectrum of Germany.

Book Applied Discriminant Analysis

Download or read book Applied Discriminant Analysis written by Carl J. Huberty and published by Wiley-Interscience. This book was released on 1994-08-11 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most books on discriminant analysis focus on statistical theory. But properly applied, discriminant analysis methods can be enormously useful in the interpretation of data. This book is the first ever to offer a complete introduction to discriminant analysis that focuses on applications. It provides numerous examples, explained in great detail, using current statistical discriminant analysis algorithms. It also develops several themes that will be useful to researchers and students regardless of the analytical methods they employ. They are the careful examination of data prior to final analysis; the application of critical judgment and common sense to all analyses and interpretations; and conducting multiple analyses as a matter of routine. To encourage and enable readers to conduct multiple analyses of their data, the accompanying diskette contains the four complete data sets and five special computer programs that are referred to repeatedly in the text and are the subjects of numerous exercise problems. This enables the reader to carry out package analyses on the data sets using a variety of procedural options both within and across computer packages. The term "discriminant analysis" means different things to different people. For statisticians and researchers in the physical sciences, it usually denotes the process through which group membership is predicted on the basis of multiple predictor variables. Behavioral scientists, on the other hand, often use discriminant analysis to describe group differences across multiple response variables. Though closely related, predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA) are used for different purposes and should be approached in different ways. To accentuate these differences and distinguish clearly between the two, Applied Discriminant Analysis presents these topics separately. For graduate students, this book will expand your background in multivariate data analysis methods and facilitate both the reading and the conducting of applied empirical research. It will also be of great use to experienced researchers who wish to enhance or update their quantitative background, and to methodologists who want to learn more about the details of applied discriminant data analysis, and some still unresolved problems, as well.

Book Discriminant analysis and applications  edited by T Cacoullos

Download or read book Discriminant analysis and applications edited by T Cacoullos written by NATO Advanced Study Institute on Discriminant Analysis and Applications, Athens, 1972 and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Contributions to linear discriminant analysis with applications to growth curves

Download or read book Contributions to linear discriminant analysis with applications to growth curves written by Edward Kanuti Ngailo and published by Linköping University Electronic Press. This book was released on 2020-05-06 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis concerns contributions to linear discriminant analysis with applications to growth curves. Firstly, we present the linear discriminant function coefficients in a stochastic representation using random variables from the standard univariate distributions. We apply the characterized distribution in the classification function to approximate the classification error rate. The results are then extended to large dimension asymptotics under assumption that the dimension p of the parameter space increases together with the sample size n to infinity such that the ratio converges to a positive constant c (0, 1). Secondly, the thesis treats repeated measures data which correspond to multiple measurements that are taken on the same subject at different time points. We develop a linear classification function to classify an individual into one out of two populations on the basis of the repeated measures data that when the means follow a growth curve structure. The growth curve structure we first consider assumes that all treatments (groups) follows the same growth profile. However, this is not necessarily true in general and the problem is extended to linear classification where the means follow an extended growth curve structure, i.e., the treatments under the experimental design follow different growth profiles. At last, a function of the inverse Wishart matrix and a normal distribution finds its application in portfolio theory where the vector of optimal portfolio weights is proportional to the product of the inverse sample covariance matrix and a sample mean vector. Analytical expressions for higher order moments and non-central moments of the portfolio weights are derived when the returns are assumed to be independently multivariate normally distributed. Moreover, the expressions for the mean, variance, skewness and kurtosis of specific estimated weights are obtained. The results are complemented using a Monte Carlo simulation study, where data from the multivariate normal and t-distributions are discussed. Den här avhandlingen studerar diskriminantanalys, klassificering av tillväxtkurvor och portföljteori. Diskriminantanalys och klassificering är flerdimensionella tekniker som används för att separera olika mängder av objekt och för att tilldela nya objekt till redan definierade grupper (så kallade klasser). En klassisk metod är att använda Fishers linjära diskriminantfunktion och när alla parametrar är kända så kan man enkelt beräkna sannolikheterna för felklassificering. Tyvärr är så sällan fallet, utan parametrarna måste skattas från data, och då blir Fishers linjära diskriminantfunktion en funktion av en Wishartmatris och multivariat normalfördelade vektorer. I den här avhandlingen studerar vi hur man kan approximativt beräkna sannolikheten för felklassificering under antagande att dimensionen på parameterrummet ökar tillsammans med antalet observationer genom att använda en särskild stokastisk representation av diskriminantfunktionen. Upprepade mätningar över tiden på samma individ eller objekt går att modellera med så kallade tillväxtkurvor. Vid klassificering av tillväxtkurvor, eller rättare sagt av upprepade mätningar för en ny individ, bör man ta tillvara på både den spatiala- och temporala informationen som finns hos dessa observationer. Vi vidareutvecklar Fishers linjära diskriminantfunktion att passa för upprepade mätningar och beräknar asymptotiska sannolikheter för felklassificering. Till sist kan man notera att snarlika funktioner av Wishartmatriser och multivariat normalfördelade vektorer dyker upp när man vill beräkna de optimala vikterna i portföljteori. Genom en stokastisk representation studerar vi egenskaperna hos portföljvikterna och gör dessutom en simuleringsstudie för att förstå vad som händer när antagandet om normalfördelning inte är uppfyllt.

Book Statistical Methods of Discrimination and Classification

Download or read book Statistical Methods of Discrimination and Classification written by Sung C. Choi and published by Elsevier. This book was released on 2014-05-17 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. The studies in the text primarily focus on various methods of discriminating and classifying variables, such as multiple discriminant analysis in the presence of mixed continuous and categorical data; choice of the smoothing parameter and efficiency of k-nearest neighbor classification; and assessing the performance of an allocation rule. The book will be of great use to researchers and practitioners of wide array of scientific disciplines, including engineering, psychology, biology, and physics.

Book Handbook Of Financial Econometrics  Mathematics  Statistics  And Machine Learning  In 4 Volumes

Download or read book Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and published by World Scientific. This book was released on 2020-07-30 with total page 5053 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

Book Biometric Image Discrimination Technologies

Download or read book Biometric Image Discrimination Technologies written by David Zhang and published by IGI Global. This book was released on 2006-01-01 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book gives an introduction to basic biometric image discrimination technologies including theories that are the foundations of those technologies and new algorithms for biometrics authentication"--Provided by publisher.

Book Discriminant analysis and applications

Download or read book Discriminant analysis and applications written by Theophilos Cacoullos and published by . This book was released on 1973 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Systems  Decision and Control in Energy III

Download or read book Systems Decision and Control in Energy III written by Artur Zaporozhets and published by Springer Nature. This book was released on 2021-11-30 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes new energy saving methods and technologies for heat power engineering. The book is devoted to topical issues of energy and related industries. Leading Ukrainian scientists from both scientific institutes and educational universities took part in its creation. The research results are presented in 6 parts: electrical engineering, heat power engineering, nuclear power engineering, fossil fuels, cybersecurity and computer science, environmental safety. Results of regulating of operating modes and applicability of model checking technique in power systems are showed. Separate block of questions regarding the functioning of nuclear power plants, their waste and preventive measures of protection against negative effects on living organisms (including, for example, the Chernobyl nuclear power plant) is considered. The results of the peculiarities of the extraction, purification and use of fossil fuels are presented. In some chapters, presented the results on improving the cybersecurity of energy systems and its resilience to various threats, including the use of 5G technology. Traditionally for this series, issues of ecological safety, the impact of different energy systems on the environment and its protection are considered. A book is for researchers, engineers, as well as lecturers and postgraduates of higher education institutions dealing with energy sector, power systems, ecological safety, etc.

Book Multiple Discriminant Analysis  Marketing Research Applications

Download or read book Multiple Discriminant Analysis Marketing Research Applications written by Richard Johnson and published by Marketing Classics Press. This book was released on 2011-06-30 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Accelerating New Food Product Design and Development

Download or read book Accelerating New Food Product Design and Development written by Jacqueline H. Beckley and published by John Wiley & Sons. This book was released on 2017-10-23 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written primarily for directors and managers of food design and development, food scientists, technologists, and product developers, this book explains all the necessary information in order to help meet the increasing demands for innovation in an industry that is providing fewer resources. This updated edition, by a group of seasoned food industry business professionals and academics, provides a real-world perspective of what is occurring in the food industry right now, offers strategic frameworks for problem solving and R&D strategies, and presents methods needed to accelerate and optimize new product development. Accelerating New Food Product Design and Development, Second Edition features five brand new chapters covering all the changes that have occurred within the last decade: A Flavor Supplier Perspective, An Ingredient Supplier Perspective, Applying Processes that Accelerate New Product Development, Looking at How the University Prepares Someone for a Career in Food, and Innovative Packaging and Its Impact on Accelerated Product Development. Offers new perspectives on what really goes on during the development process Includes updated chapters fully describing the changes that have occurred in the food industry, both from a developer’s point of view as well as the consumer requirements Features a completely rewritten chapter covering the importance of packaging which is enhanced through 3D printing All of this against the impact on speed to market Filled with unique viewpoints of the business from those who really know and a plethora of new information, Accelerating New Food Product Design and Development, Second Edition will be of great interest to all professionals engaged in new food product design and development.

Book Discriminant Analysis and Clustering

Download or read book Discriminant Analysis and Clustering written by Ram Gnanadesikan and published by National Academies Press. This book was released on 1988-01-01 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Multi  and Megavariate Data Analysis Basic Principles and Applications

Download or read book Multi and Megavariate Data Analysis Basic Principles and Applications written by L. Eriksson and published by Umetrics Academy. This book was released on 2013-07-01 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.